OpenRaiser/Intern-Atlas huggingface dataset:
Seek and Decode: Random Access with Physical-Layer Network Coding and Multiuser Detection
Venue: arXiv cs.NI 2014
Year: 2014

We present a novel cross layer approach to random access (RA) that combines physical-layer network coding (PLNC) with multiuser detection (MUD). PLNC and MUD are applied jointly at the physical level in order to extract any linear combination of messages experiencing a collision. The set of combinations extracted from a whole frame is then processed by the receiver to recover the original packets. A simple pre-coding stage at the transmitting terminals allows the receiver to further increase system diversity. We derive an analytical bound on the system throughput and present simulation results for the decoding at the physical level as well as several performance measures at frame level in block fading channels, namely throughput, packet loss rate and energy efficiency. The results we present are promising and suggest that a cross layer approach leveraging on the joint use of PLNC and MUD can significantly improve the performance of RA systems.
Beam-forming for Secure Communication in Amplify-and-Forward Networks: An SNR based approach
Venue: arXiv cs.CR 2014
Year: 2014

The problem of secure communication in Amplify-and-Forward (AF) relay networks with multiple eavesdroppers is considered. Assuming that a receiver (destination or eavesdropper) can decode a message only if the received SNR is above a predefined threshold, we introduce SNR based optimization formulations to calculate optimal scaling factors for relay nodes in two scenarios. In the first scenario, we maximize the achievable rate at the legitimate destination, subject to the condition that the received SNR at each eavesdropper is below the target threshold. Due to the non-convex nature of the objective function and eavesdroppers' constraints, we transform variables and obtain a Quadratically Constrained Quadratic Program (QCQP) with convex constraints, which can be solved efficiently. When the constraints are not convex, we consider a Semi-definite relaxation (SDR). In the second scenario, we minimize the total power consumed by all relay nodes, subject to the condition that the received SNR at the legitimate destination is above the threshold and at every eavesdropper, it is below the corresponding threshold. We propose a semi-definite relaxation of the problem in this scenario and also provide an analytical lower bound.
"Infographics" team: Selecting Control Parameters via Maximal Fisher Information
Venue: arXiv cs.IT 2014
Year: 2014

Team description paper for RoboCup 2014 Soccer Simulation League 2D.
Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array
Venue: arXiv cs.NE 2014
Year: 2014

Recent advances in neuroscience together with nanoscale electronic device technology have resulted in huge interests in realizing brain-like computing hardwares using emerging nanoscale memory devices as synaptic elements. Although there has been experimental work that demonstrated the operation of nanoscale synaptic element at the single device level, network level studies have been limited to simulations. In this work, we demonstrate, using experiments, array level associative learning using phase change synaptic devices connected in a grid like configuration similar to the organization of the biological brain. Implementing Hebbian learning with phase change memory cells, the synaptic grid was able to store presented patterns and recall missing patterns in an associative brain-like fashion. We found that the system is robust to device variations, and large variations in cell resistance states can be accommodated by increasing the number of training epochs. We illustrated the tradeoff between variation tolerance of the network and the overall energy consumption, and found that energy consumption is decreased significantly for lower variation tolerance.
Consistently Orienting Facets in Polygon Meshes by Minimizing the Dirichlet Energy of Generalized Winding Numbers
Venue: arXiv cs.GR 2014
Year: 2014

Jacobson et al. [JKSH13] hypothesized that the local coherency of the generalized winding number function could be used to correctly determine consistent facet orientations in polygon meshes. We report on an approach to consistently orienting facets in polygon meshes by minimizing the Dirichlet energy of generalized winding numbers. While the energy can be concisely formulated and efficiently computed, we found that this approach is fundamentally flawed and is unfortunately not applicable for most handmade meshes shared on popular mesh repositories such as Google 3D Warehouse.
The tropical shadow-vertex algorithm solves mean payoff games in polynomial time on average
Venue: arXiv cs.GT 2014
Year: 2014

We introduce an algorithm which solves mean payoff games in polynomial time on average, assuming the distribution of the games satisfies a flip invariance property on the set of actions associated with every state. The algorithm is a tropical analogue of the shadow-vertex simplex algorithm, which solves mean payoff games via linear feasibility problems over the tropical semiring $(\mathbb{R} \cup \{-\infty\}, \max, +)$. The key ingredient in our approach is that the shadow-vertex pivoting rule can be transferred to tropical polyhedra, and that its computation reduces to optimal assignment problems through Plücker relations.
Operational Distributed Regulation for Bitcoin
Venue: arXiv cs.CR 2014
Year: 2014

On February 2014, $650.000.000 worth of Bitcoins disappeared. Currently it is unclear whether hackers or MtGox, the largest Bitcoin exchange, are to be blamed. In either case, the anonymous and unregulated nature of the Bitcoin system makes it practically impossible for innocent victims to get their money back. We have investigated the technical possibilities, solutions and implications of introducing a regulatory framework based on redlisting Bitcoin accounts. Despite numerous proposals, the Bitcoin community has voiced a strong opinion against any form of regulation. However, most of the discussions were based on speculations rather than facts. We strive to contribute a scientific foundation to these discussions and illuminate the path to crypto-justice.
Performance Comparison of Contention- and Schedule-based MAC Protocols in Urban Parking Sensor Networks
Venue: arXiv cs.NI 2014
Year: 2014

Network traffic model is a critical problem for urban applications, mainly because of its diversity and node density. As wireless sensor network is highly concerned with the development of smart cities, careful consideration to traffic model helps choose appropriate protocols and adapt network parameters to reach best performances on energy-latency tradeoffs. In this paper, we compare the performance of two off-the-shelf medium access control protocols on two different kinds of traffic models, and then evaluate their application-end information delay and energy consumption while varying traffic parameters and network density. From the simulation results, we highlight some limits induced by network density and occurrence frequency of event-driven applications. When it comes to realtime urban services, a protocol selection shall be taken into account - even dynamically - with a special attention to energy-delay tradeoff. To this end, we provide several insights on parking sensor networks.
Fast Edge Detection Using Structured Forests
Venue: arXiv cs.CV 2014
Year: 2014

Edge detection is a critical component of many vision systems, including object detectors and image segmentation algorithms. Patches of edges exhibit well-known forms of local structure, such as straight lines or T-junctions. In this paper we take advantage of the structure present in local image patches to learn both an accurate and computationally efficient edge detector. We formulate the problem of predicting local edge masks in a structured learning framework applied to random decision forests. Our novel approach to learning decision trees robustly maps the structured labels to a discrete space on which standard information gain measures may be evaluated. The result is an approach that obtains realtime performance that is orders of magnitude faster than many competing state-of-the-art approaches, while also achieving state-of-the-art edge detection results on the BSDS500 Segmentation dataset and NYU Depth dataset. Finally, we show the potential of our approach as a general purpose edge detector by showing our learned edge models generalize well across datasets.
Guidelines to minimize cost of software quality in agile scrum process
Venue: arXiv cs.SE 2014
Year: 2014

This paper presents a case study of Agile Scrum process followed in Retail Domain project. This paper also reveals the impacts of Cost of Software Quality, when agile scrum process is not followed efficiently. While analyzing the case study, the gaps were found and guidelines for process improvements were also suggested in this paper.
Environmental Sensing by Wearable Device for Indoor Activity and Location Estimation
Venue: arXiv cs.HC 2014
Year: 2014

We present results from a set of experiments in this pilot study to investigate the causal influence of user activity on various environmental parameters monitored by occupant carried multi-purpose sensors. Hypotheses with respect to each type of measurements are verified, including temperature, humidity, and light level collected during eight typical activities: sitting in lab / cubicle, indoor walking / running, resting after physical activity, climbing stairs, taking elevators, and outdoor walking. Our main contribution is the development of features for activity and location recognition based on environmental measurements, which exploit location- and activity-specific characteristics and capture the trends resulted from the underlying physiological process. The features are statistically shown to have good separability and are also information-rich. Fusing environmental sensing together with acceleration is shown to achieve classification accuracy as high as 99.13%. For building applications, this study motivates a sensor fusion paradigm for learning individualized activity, location, and environmental preferences for energy management and user comfort.
Computational Complexity of Certifying Restricted Isometry Property
Venue: arXiv cs.CC 2014
Year: 2014

Given a matrix $A$ with $n$ rows, a number $k<n$, and $0<δ< 1$, $A$ is $(k,δ)$-RIP (Restricted Isometry Property) if, for any vector $x \in \mathbb{R}^n$, with at most $k$ non-zero co-ordinates, $$(1-δ) \|x\|_2 \leq \|A x\|_2 \leq (1+δ)\|x\|_2$$ In many applications, such as compressed sensing and sparse recovery, it is desirable to construct RIP matrices with a large $k$ and a small $δ$. Given the efficacy of random constructions in generating useful RIP matrices, the problem of certifying the RIP parameters of a matrix has become important. In this paper, we prove that it is hard to approximate the RIP parameters of a matrix assuming the Small-Set-Expansion-Hypothesis. Specifically, we prove that for any arbitrarily large constant $C>0$ and any arbitrarily small constant $0<δ<1$, there exists some $k$ such that given a matrix $M$, it is SSE-Hard to distinguish the following two cases: - (Highly RIP) $M$ is $(k,δ)$-RIP. - (Far away from RIP) $M$ is not $(k/C, 1-δ)$-RIP. Most of the previous results on the topic of hardness of RIP certification only hold for certification when $δ=o(1)$. In practice, it is of interest to understand the complexity of certifying a matrix with $δ$ being close to $\sqrt{2}-1$, as it suffices for many real applications to have matrices with $δ= \sqrt{2}-1$. Our hardness result holds for any constant $δ$. Specifically, our result proves that even if $δ$ is indeed very small, i.e. the matrix is in fact \emph{strongly RIP}, certifying that the matrix exhibits \emph{weak RIP} itself is SSE-Hard. In order to prove the hardness result, we prove a variant of the Cheeger's Inequality for sparse vectors.
Three-Party Energy Management With Distributed Energy Resources in Smart Grid
Venue: arXiv cs.SY 2014
Year: 2014

In this paper, the benefits of distributed energy resources (DERs) are considered in an energy management scheme for a smart community consisting of a large number of residential units (RUs) and a shared facility controller (SFC). A non-cooperative Stackelberg game between RUs and the SFC is proposed in order to explore how both entities can benefit, in terms of achieved utility and minimizing total cost respectively, from their energy trading with each other and the grid. From the properties of the game, it is shown that the maximum benefit to the SFC in terms of reduction in total cost is obtained at the unique and strategy proof Stackelberg equilibrium (SE). It is further shown that the SE is guaranteed to be reached by the SFC and RUs by executing the proposed algorithm in a distributed fashion, where participating RUs comply with their best strategies in response to the action chosen by the SFC. In addition, a charging-discharging scheme is introduced for the SFC's storage device (SD) that can further lower the SFC's total cost if the proposed game is implemented. Numerical experiments confirm the effectiveness of the proposed scheme.
A Unified Quantitative Model of Vision and Audition
Venue: arXiv cs.CV 2014
Year: 2014

We have put forwards a unified quantitative framework of vision and audition, based on existing data and theories. According to this model, the retina is a feedforward network self-adaptive to inputs in a specific period. After fully grown, cells become specialized detectors based on statistics of stimulus history. This model has provided explanations for perception mechanisms of colour, shape, depth and motion. Moreover, based on this ground we have put forwards a bold conjecture that single ear can detect sound direction. This is complementary to existing theories and has provided better explanations for sound localization.
BSTree: an Incremental Indexing Structure for Similarity Search and Real Time Monitoring of Data Streams
Venue: arXiv cs.DB 2014
Year: 2014

In this work, a new indexing technique of data streams called BSTree is proposed. This technique uses the method of data discretization, SAX [4], to reduce online the dimensionality of data streams. It draws on Btree to build the index and finally uses an LRV (least Recently visited) pruning technique to rid the index structure from data whose last visit time exceeds a threshold value and thus minimizes response time for similarity search queries.
Committees of deep feedforward networks trained with few data
Venue: arXiv cs.CV 2014
Year: 2014

Deep convolutional neural networks are known to give good results on image classification tasks. In this paper we present a method to improve the classification result by combining multiple such networks in a committee. We adopt the STL-10 dataset which has very few training examples and show that our method can achieve results that are better than the state of the art. The networks are trained layer-wise and no backpropagation is used. We also explore the effects of dataset augmentation by mirroring, rotation, and scaling.
Preemptive Thread Block Scheduling with Online Structural Runtime Prediction for Concurrent GPGPU Kernels
Venue: arXiv cs.AR 2014
Year: 2014

Recent NVIDIA Graphics Processing Units (GPUs) can execute multiple kernels concurrently. On these GPUs, the thread block scheduler (TBS) uses the FIFO policy to schedule their thread blocks. We show that FIFO leaves performance to chance, resulting in significant loss of performance and fairness. To improve performance and fairness, we propose use of the preemptive Shortest Remaining Time First (SRTF) policy instead. Although SRTF requires an estimate of runtime of GPU kernels, we show that such an estimate of the runtime can be easily obtained using online profiling and exploiting a simple observation on GPU kernels' grid structure. Specifically, we propose a novel Structural Runtime Predictor. Using a simple Staircase model of GPU kernel execution, we show that the runtime of a kernel can be predicted by profiling only the first few thread blocks. We evaluate an online predictor based on this model on benchmarks from ERCBench, and find that it can estimate the actual runtime reasonably well after the execution of only a single thread block. Next, we design a thread block scheduler that is both concurrent kernel-aware and uses this predictor. We implement the SRTF policy and evaluate it on two-program workloads from ERCBench. SRTF improves STP by 1.18x and ANTT by 2.25x over FIFO. When compared to MPMax, a state-of-the-art resource allocation policy for concurrent kernels, SRTF improves STP by 1.16x and ANTT by 1.3x. To improve fairness, we also propose SRTF/Adaptive which controls resource usage of concurrently executing kernels to maximize fairness. SRTF/Adaptive improves STP by 1.12x, ANTT by 2.23x and Fairness by 2.95x compared to FIFO. Overall, our implementation of SRTF achieves system throughput to within 12.64% of Shortest Job First (SJF, an oracle optimal scheduling policy), bridging 49% of the gap between FIFO and SJF.
Cognitive Surveillance: Why does it never appear among the AVSS Conferences topics?
Venue: arXiv cs.AI 2014
Year: 2014

Video Surveillance is a fast evolving field of research and development (R&D) driven by the urgent need for public security and safety (due to the growing threats of terrorism, vandalism, and anti-social behavior). Traditionally, surveillance systems are comprised of two components - video cameras distributed over the guarded area and human observer watching and analyzing the incoming video. Explosive growth of installed cameras and limited human operator's ability to process the delivered video content raise an urgent demand for developing surveillance systems with human like cognitive capabilities, that is - Cognitive surveillance systems. The growing interest in this issue is testified by the tens of workshops, symposiums and conferences held over the world each year. The IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS) is certainly one of them. However, for unknown reasons, the term Cognitive Surveillance does never appear among its topics. As to me, the explanation for this is simple - the complexity and the indefinable nature of the term "Cognition". In this paper, I am trying to resolve the problem providing a novel definition of cognition equally suitable for biological as well as technological applications. I hope my humble efforts will be helpful.
Group Communication Patterns for High Performance Computing in Scala
Venue: arXiv cs.PL 2014
Year: 2014

We developed a Functional object-oriented Parallel framework (FooPar) for high-level high-performance computing in Scala. Central to this framework are Distributed Memory Parallel Data structures (DPDs), i.e., collections of data distributed in a shared nothing system together with parallel operations on these data. In this paper, we first present FooPar's architecture and the idea of DPDs and group communications. Then, we show how DPDs can be implemented elegantly and efficiently in Scala based on the Traversable/Builder pattern, unifying Functional and Object-Oriented Programming. We prove the correctness and safety of one communication algorithm and show how specification testing (via ScalaCheck) can be used to bridge the gap between proof and implementation. Furthermore, we show that the group communication operations of FooPar outperform those of the MPJ Express open source MPI-bindings for Java, both asymptotically and empirically. FooPar has already been shown to be capable of achieving close-to-optimal performance for dense matrix-matrix multiplication via JNI. In this article, we present results on a parallel implementation of the Floyd-Warshall algorithm in FooPar, achieving more than 94 % efficiency compared to the serial version on a cluster using 100 cores for matrices of dimension 38000 x 38000.
Saccadic Eye Movements and the Generalized Pareto Distribution
Venue: arXiv cs.CV 2014
Year: 2014

We describe a statistical analysis of the eye tracker measurements in a database with 15 observers viewing 1003 images under free-viewing conditions. In contrast to the common approach of investigating the properties of the fixation points we analyze the properties of the transition phases between fixations. We introduce hyperbolic geometry as a tool to measure the step length between consecutive eye positions. We show that the step lengths, measured in hyperbolic and euclidean geometry, follow a generalized Pareto distribution. The results based on the hyperbolic distance are more robust than those based on euclidean geometry. We show how the structure of the space of generalized Pareto distributions can be used to characterize and identify individual observers.
Experimental Investigation of Control Updating Period Monitoring In Industrial PLC-based Fast MPC: Application to The Constrained Control of a Cryogenic Refrigerator
Venue: arXiv cs.SY 2014
Year: 2014

In this paper, a complete industrial validation of a recently published scheme for on-line adaptation of the control updating period in Model Predictive Control is proposed. The industrial process that serves in the validation is a cryogenic refrigerator that is used to cool the supra-conductors involved in particle accelerators or experimental nuclear reactors. Two recently predicted features are validated: the first states that it is sometimes better to use less efficient (per iteration) optimizer if the lack of efficiency is over-compensated by an increase in the updating control frequency. The second is that for a given solver, it is worth monitoring the control updating period based on the on-line measured behavior of the cost function.
Power-Optimal Feedback-Based Random Spectrum Access for an Energy Harvesting Cognitive User
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we study and analyze cognitive radio networks in which secondary users (SUs) are equipped with Energy Harvesting (EH) capability. We design a random spectrum sensing and access protocol for the SU that exploits the primary link's feedback and requires less average sensing time. Unlike previous works proposed earlier in literature, we do not assume perfect feedback. Instead, we take into account the more practical possibilities of overhearing unreliable feedback signals and accommodate spectrum sensing errors. Moreover, we assume an interference-based channel model where the receivers are equipped with multi-packet reception (MPR) capability. Furthermore, we perform power allocation at the SU with the objective of maximizing the secondary throughput under constraints that maintain certain quality-of-service (QoS) measures for the primary user (PU).
On the Complexity of Clustered-Level Planarity and T-Level Planarity
Venue: arXiv cs.DS 2014
Year: 2014

In this paper we study two problems related to the drawing of level graphs, that is, T-LEVEL PLANARITY and CLUSTERED-LEVEL PLANARITY. We show that both problems are NP-complete in the general case and that they become polynomial-time solvable when restricted to proper instances.